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Record W1988558394 · doi:10.1177/1534650108319915

Errorless Priming

2008· article· en· W1988558394 on OpenAlex
Anthony Folino, Joseph M. Ducharme, Nathalie K. Conn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Case Studies · 2008
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychologyAntecedent (behavioral psychology)Priming (agriculture)AggressionIntervention (counseling)Developmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Reactive aggressive children experience social encoding and interpretation difficulties. Such deficits increase the likelihood that reactive aggressive children perceive the actions of others as provocative and respond in an aggressive manner. Errorless priming was developed as a proactive and success-focused treatment for an 8-year-old boy demonstrating severe reactive aggression (RA). Observations of the child revealed several antecedents that immediately preceded his aggression. This information enabled prediction of aggressive outbursts and development of an intervention that involved providing the child with preparatory information (i.e., priming statements) to moderate his reaction to upcoming stressors. As is characteristic of errorless approaches, a graduated hierarchy was used to systematically fade priming statements. Following treatment, the child was able to tolerate, without problem behavior, antecedent conditions that he found challenging prior to treatment. Errorless priming may have broad potential as a brief and time-efficient intervention for RA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.256
GPT teacher head0.481
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it